Abnormal oscillatory synchronisation in the motor system leads to impaired movement

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Objective. Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigations into the neural mechanisms governing amygdaloid motor movement and inhibition. This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between 'Go' and 'No-go' trials of an arm-reaching task.Approach. Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a direct reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-correctedZtests were used to assess significant modulations of beta power between the Response and fixation (baseline) phases in the 'Go' and 'No-go' conditions.Main results. In the 'Go' condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p⩽ 0.0499). In the 'No-go' condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the response phase (p⩽ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the 'Go' and 'No-go' conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.Significance.This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

Objective.Can we classify movement execution and inhibition from hippocampal oscillations during arm-reaching tasks? Traditionally associated with memory encoding, spatial navigation, and motor sequence consolidation, the hippocampus has come under scrutiny for its potential role in movement processing. Stereotactic electroencephalography (SEEG) has provided a unique opportunity to study the neurophysiology of the human hippocampus during motor tasks. In this study, we assess the accuracy of discriminant functions, in combination with principal component analysis (PCA), in classifying between 'Go' and 'No-go' trials in a Go/No-go arm-reaching task.Approach.Our approach centers on capturing the modulation of beta-band (13-30 Hz) power from multiple SEEG contacts in the hippocampus and minimizing the dimensional complexity of channels and frequency bins. This study utilizes SEEG data from the human hippocampus of 10 participants diagnosed with epilepsy. Spectral power was computed during a 'center-out' Go/No-go arm-reaching task, where participants reached or withheld their hand based on a colored cue. PCA was used to reduce data dimension and isolate the highest-variance components within the beta band. The Silhouette score was employed to measure the quality of clustering between 'Go' and 'No-go' trials. The accuracy of five different discriminant functions was evaluated using cross-validation.Main results.The Diagonal-Quadratic model performed best of the 5 classification models, exhibiting the lowest error rate in all participants (median: 9.91%, average: 14.67%). PCA showed that the first two principal components collectively accounted for 54.83% of the total variance explained on average across all participants, ranging from 36.92% to 81.25% among participants.Significance.This study shows that PCA paired with a Diagonal-Quadratic model can be an effective method for classifying between Go/No-go trials from beta-band power in the hippocampus during arm-reaching responses. This emphasizes the significance of hippocampal beta-power modulation in motor control, unveiling its potential implications for brain-computer interface applications.

Beta-frequency sensory stimulation enhances gait rhythmicity through strengthened coupling between striatal networks and stepping movement

Stepping movement is delta (1-4 Hz) rhythmic and depends on sensory inputs. In addition to delta rhythms, beta (10-30 Hz) frequency dynamics are also prominent in the motor circuits and are coupled to neuronal delta rhythms both at the network and the cellular levels. Since beta rhythms are broadly supported by cortical and subcortical sensorimotor circuits, we explore how beta-frequency sensory stimulation influences delta-rhythmic stepping movement, and dorsal striatal circuit regulation of stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz to mice voluntarily locomoting, while simultaneously recording stepping movement, striatal cellular calcium dynamics and local field potentials (LFPs). We found that 10 Hz, but not 145 Hz stimulation prominently entrained striatal LFPs. Even though sensory stimulation at both frequencies promoted locomotion and desynchronized striatal network, only 10 Hz stimulation enhanced the delta rhythmicity of stepping movement and strengthened the coupling between stepping and striatal LFP delta and beta oscillations. These results demonstrate that higher frequency sensory stimulation can modulate lower frequency dorsal striatal neural dynamics and improve stepping rhythmicity, highlighting the translational potential of non-invasive beta-frequency sensory stimulation for improving gait.

[Dynamic activity model of movement disorders: a unified view to understand their pathophysiology]

Malfunction of the basal ganglia leads to movement disorders such as Parkinson's disease, dystonia, Huntington's disease, dyskinesia, and hemiballism, but their underlying pathophysiology is still subject to debate. To understand their pathophysiology in a unified manner, we propose the "dynamic activity model", on the basis of alterations of cortically induced responses in individual nuclei of the basal ganglia. In the normal state, electric stimulation in the motor cortex, mimicking cortical activity during initiation of voluntary movements, evokes a triphasic response consisting of early excitation, inhibition, and late excitation in the output stations of the basal ganglia of monkeys, rodents, and humans. Among three components, cortically induced inhibition, which is mediated by the direct pathway, releases an appropriate movement at an appropriate time by disinhibiting thalamic and cortical activity, whereas early and late excitation, which is mediated by the hyperdirect and indirect pathways, resets on-going cortical activity and stops movements, respectively. Cortically induced triphasic response patterns are systematically altered in various movement disorder models and could well explain the pathophysiology of their motor symptoms. In monkey and mouse models of Parkinson's disease, cortically induced inhibition is reduced and prevents the release of movements, resulting in akinesia/bradykinesia. On the other hand, in a mouse model of dystonia, cortically induced inhibition is enhanced and releases unintended movements, inducing involuntary muscle contractions. Moreover, after blocking the subthalamic nucleus activity in a monkey model of Parkinson's disease, cortically induced inhibition is recovered and enables voluntary movements, explaining the underlying mechanism of stereotactic surgery to ameliorate parkinsonian motor signs. The "dynamic activity model" gives us a more comprehensive view of the pathophysiology underlying motor symptoms of movement disorders and clues for their novel therapies.

Computational models advance deep brain stimulation for Parkinson's disease

Deep brain stimulation(DBS) has become an effective intervention for advanced Parkinson's disease(PD), but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia (BG), the abnormal pathological changes of the BG in PD, and how computational models can help understand and advance DBS. We also describe two types of models: mathematical theoretical models and clinical predictive models. Mathematical theoretical models simulate neurons or neural networks of BG to shed light on the mechanistic principle underlying DBS, while clinical predictive models focus more on patients' outcomes, helping to adapt treatment plans for each patient and advance novel electrode designs. Finally, we provide insights and an outlook on future technologies.

The dual role of striatal interneurons: circuit modulation and trophic support for the basal ganglia

ABSTRACT

Striatal interneurons play a key role in modulating striatal-dependent behaviors, including motor activity and reward and emotional processing. Interneurons not only provide modulation to the basal ganglia circuitry under homeostasis but are also involved in changes to plasticity and adaptation during disease conditions such as Parkinson's or Huntington's disease. This review aims to summarize recent findings regarding the role of striatal cholinergic and GABAergic interneurons in providing circuit modulation to the basal ganglia in both homeostatic and disease conditions. In addition to direct circuit modulation, striatal interneurons have also been shown to provide trophic support to maintain neuron populations in adulthood. We discuss this interesting and novel role of striatal interneurons, with a focus on the maintenance of adult dopaminergic neurons from interneuron-derived sonic-hedgehog.

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.

Sensorimotor Oscillations in Human Infants during an Innate Rhythmic Movement

The relationship between cerebral rhythms and early sensorimotor development is not clear. In recent decades, evidence revealed a rhythmic modulation involving sensorimotor processing. A widely corroborated functional role of oscillatory activity is to coordinate the information flow across sensorimotor networks. Their activity is coordinated by event-related synchronisation and desynchronisation in different sensorimotor rhythms, which indicate parallel processes may be occurring in the neuronal network during movement. To date, the dynamics of these brain oscillations and early sensorimotor development are unexplored. Our study investigates the relationship between the cerebral rhythms using EEG and a typical rhythmic movement of infants, the non-nutritive sucking (NNS) behaviour. NNS is an endogenous behaviour that originates from the suck central pattern generator in the brainstem. We find, in 17 infants, that sucking frequency correlates with beta synchronisation within the sensorimotor area in two phases: one strongly anticipating (~3 s) and the other encompassing the start of the motion. These findings suggest that a beta synchronisation of the sensorimotor cortex may influence the sensorimotor dynamics of NNS activity. Our results reveal the importance of rapid brain oscillations in infants and the role of beta synchronisation and their possible role in the communication between cortical and deep generators.

The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition

Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD.

A Systematic Review of Neurophysiology-Based Localization Techniques Used in Deep Brain Stimulation Surgery of the Subthalamic Nucleus

OBJECTIVE

This systematic review is conducted to identify, compare, and analyze neurophysiological feature selection, extraction, and classification to provide a comprehensive reference on neurophysiology-based subthalamic nucleus (STN) localization.

MATERIALS AND METHODS

The review was carried out using the methods and guidelines of the Kitchenham systematic review and provides an in-depth analysis on methods proposed on STN localization discussed in the literature between 2000 and 2021. Three research questions were formulated, and 115 publications were identified to answer the questions.

RESULTS

The three research questions formulated are answered using the literature found on the respective topics. This review discussed the technologies used in past research, and the performance of the state-of-the-art techniques is also reviewed.

CONCLUSION

This systematic review provides a comprehensive reference on neurophysiology-based STN localization by reviewing the research questions other new researchers may also have.

On-Off and Proportional Closed-Loop Adaptive Deep Brain Stimulation Reduces Motor Symptoms in Freely Moving Hemiparkinsonian Rats

OBJECTIVES

Closed-loop adaptive deep brain stimulation (aDBS) continuously adjusts stimulation parameters, with the potential to improve efficacy and reduce side effects of deep brain stimulation (DBS) for Parkinson's disease (PD). Rodent models can provide an effective platform for testing aDBS algorithms and establishing efficacy before clinical investigation. In this study, we compare two aDBS algorithms, on-off and proportional modulation of DBS amplitude, with conventional DBS in hemiparkinsonian rats.

MATERIALS AND METHODS

DBS of the subthalamic nucleus (STN) was delivered wirelessly in freely moving male and female hemiparkinsonian (N = 7) and sham (N = 3) Wistar rats. On-off and proportional aDBS, based on STN local field potential beta power, were compared with conventional DBS and three control stimulation algorithms. Behavior was assessed during cylinder tests (CT) and stepping tests (ST). Successful model creation was confirmed via apomorphine-induced rotation test and Tyrosine Hydroxylase-immunocytochemistry. Electrode location was histologically confirmed. Data were analyzed using linear mixed models.

RESULTS

Contralateral paw use in parkinsonian rats was reduced to 20% and 25% in CT and ST, respectively. Conventional, on-off, and proportional aDBS significantly improved motor function, restoring contralateral paw use to approximately 45% in both tests. No improvement in motor behavior was observed with either randomly applied on-off or low-amplitude continuous stimulation. Relative STN beta power was suppressed during DBS. Relative power in the alpha and gamma bands decreased and increased, respectively. Therapeutically effective adaptive DBS used approximately 40% less energy than did conventional DBS.

CONCLUSIONS

Adaptive DBS, using both on-off and proportional control schemes, is as effective as conventional DBS in reducing motor symptoms of PD in parkinsonian rats. Both aDBS algorithms yield substantial reductions in stimulation power. These findings support using hemiparkinsonian rats as a viable model for testing aDBS based on beta power and provide a path to investigate more complex closed-loop algorithms in freely behaving animals.

Removal of electrical stimulus artifact in local field potential recorded from subthalamic nucleus by using manifold denoising

BACKGROUND

Deep brain stimulation (DBS) is an effective treatment for movement disorders such as Parkinson's disease (PD). However, local field potentials (LFPs) recorded through lead externalization during high-frequency stimulation (HFS) are contaminated by stimulus artifacts, which require to be removed before further analysis.

NEW METHOD

In this study, a novel stimulus artifact removal algorithm based on manifold denoising, termed Shrinkage and Manifold-based Artifact Removal using Template Adaptation (SMARTA), was proposed to remove artifacts by deriving a template for each stimulus artifact and subtracting it from the signal. Under a low-dimensional manifold assumption, a matrix denoising technique called optimal shrinkage was applied to design a similarity metric such that the template for stimulus artifacts could be accurately recovered.

RESULT

SMARTA was evaluated using semirealistic signals, which were the combination of semirealistic stimulus artifacts recorded in an agar brain model and LFPs of PD patients with no stimulation, and realistic LFP signals recorded in patients with PD during HFS. The results indicated that SMARTA removes stimulus artifacts with a modest distortion in LFP estimates.

COMPARISON WITH EXISTING METHODS

SMARTA was compared with moving-average subtraction, sample-and-interpolate technique, and Hampel filtering.

CONCLUSION

The proposed SMARTA algorithm helps the exploration of the neurophysiological mechanisms of DBS effects.

Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson's disease

Biomarkers obtained from the neurophysiological signals of patients with Parkinson's disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prominent cortical biomarkers of PD have typically been derived from various β band wave features. This study approached the topic from an alternative perspective and attempted to estimate a recently suggested measure representing α band nonlinear autocorrelative memory from a publicly available EEG dataset that involves 15 patients with earlier-stage PD (dopaminergic medication OFF and ON states) and 16 age-matched healthy controls. The cortical nonlinearity was elevated for the PD ON state compared with the OFF state for bilateral sensorimotor channels C3 and C4 (n = 26; P = 0.003). A similar statistical difference was also identified between PD OFF state and healthy subjects (n = 26; P = 0.049). Analysis over all channels revealed that the α band nonlinearity induced upon medication was constrained to sensorimotor regions. The α nonlinearity measure was compared with a well-accepted cortical biomarker of β-γ phase-amplitude coupling (PAC). They were in moderate negative correlation (r = -0.412; P = 0.036) for only healthy subjects, but not for the patients. The nonlinearity measure was found to be insusceptible to the nonstationary variations within the particular data. Our study provides further evidence that the α band nonlinearity measure can serve as a promising cortical biomarker of PD. The suggested measure can be estimated from a noninvasive low-resolution single scalp EEG channel of patients with relatively early-stage PD, who did not yet need to undergo deep brain stimulation operation.NEW & NOTEWORTHY This study suggests a nonlinearity measure that differentiates Parkinson's disease (PD) dopamine OFF-state scalp EEG data from those of dopamine ON-state patients and healthy subjects. Unlike typical PD cortical biomarkers based on β band activity, this metric shows elevation upon dopaminergic medication in the α band. We provide evidence supporting its potential as an early-stage promising PD biomarker that can be estimated from noninvasive EEG recordings with low resolution and SNR.

Active and Passive Cycling Decrease Subthalamic β Oscillations in Parkinson's Disease

BACKGROUND

Preserved cycling capabilities in patients with Parkinson's disease, especially in those with freezing of gait are still poorly understood. Previous research with invasive local field potential recordings in the subthalamic nucleus has shown that cycling causes a stronger suppression of β oscillations compared to walking, which facilitates motor continuation.

METHODS

We recorded local field potentials from 12 patients with Parkinson's disease (six without freezing of gait, six with freezing of gait) who were bilaterally implanted with deep brain stimulation electrodes in the subthalamic nucleus. We investigated β (13-30 Hz) and high γ (60-100 Hz) power during both active and passive cycling with different cadences and compared patients with and without freezing of gait. The passive cycling experiment, where a motor provided a fixed cadence, allowed us to study the effect of isolated sensory inputs without physical exercise.

RESULTS

We found similarly strong suppression of pathological β activity for both active and passive cycling. In contrast, there was stronger high γ band activity for active cycling. Notably, the effects of active and passive cycling were all independent of cadence. Finally, β suppression was stronger for patients with freezing of gait, especially during passive cycling.

CONCLUSIONS

Our results provide evidence for a link between proprioceptive input during cycling and β suppression. These findings support the role of continuous external sensory input and proprioceptive feedback during rhythmic passive cycling movements and suggest that systematic passive mobilization might hold therapeutic potential. © 2023 International Parkinson and Movement Disorder Society.

Striatal Neurons Are Recruited Dynamically into Collective Representations of Self-Initiated and Learned Actions in Freely Moving Mice

Striatal spiny projection neurons are hyperpolarized-at-rest (HaR) and driven to action potential threshold by a small number of powerful inputs-an input-output configuration that is detrimental to response reliability. Because the striatum is important for habitual behaviors and goal-directed learning, we conducted a microendoscopic imaging in freely moving mice that express a genetically encoded Ca2+ indicator sparsely in striatal HaR neurons to evaluate their response reliability during self-initiated movements and operant conditioning. The sparse expression was critical for longitudinal studies of response reliability, and for studying correlations among HaR neurons while minimizing spurious correlations arising from contamination by the background signal. We found that HaR neurons are recruited dynamically into action representation, with distinct neuronal subsets being engaged in a moment-by-moment fashion. While individual neurons respond with little reliability, the population response remained stable across days. Moreover, we found evidence for the temporal coupling between neuronal subsets during conditioned (but not innate) behaviors.

Increased expression of Nav1.6 of reactive astrocytes in the globus pallidus is closely associated with motor deficits in a model of Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative disease in elderly people, which is characterized by motor disabilities in PD patients. Nav1.6 is the most abundant subtype of voltage-gated sodium channels (VGSCs) in the brain of adult mammals and rodents. Here we investigated the role of Nav1.6 in the external globus pallidus (GP) involved in the pathogenesis of motor deficits in unilateral 6-OHDA(6-hydroxydopamine)lesioned rats. The results show that Nav1.6 is dramatically increased in reactive astrocytes of the ipsilateral GP in the middle stage, but not different from the control rats in the later stage of the pathological process in 6-OHDA lesioned rats. Furthermore, the down-regulation of Nav1.6 expression in the ipsilateral GP can significantly improve motor deficits in 6-OHDA lesioned rats in the middle stage of the pathological process. The electrophysiological experiments show that the down-regulation of Nav1.6 expression in the ipsilateral GP significantly decreases the abnormal high synchronization between the ipsilateral M1 (the primary motor cortex) and GP in 6-OHDA lesioned rats. Ca2+ imaging reveals that the down-regulation of Nav1.6 expression reduces the intracellular concentration of Ca2+ ([Ca2+ ]i) in primary cultured astrocytes. These findings suggest that the increased Nav1.6 expression of reactive astrocytes in the GP play an important role in the pathogenesis of motor dysfunction in the middle stage in 6-OHDA lesioned rats, which may participate in astrocyte-neuron communication by regulating [Ca2+ ]i of astrocytes, thereby contributing to the formation of abnormal electrical signals of the basal ganglia (BG) in 6-OHDA lesioned rats.

Neurophysiological mechanisms of deep brain stimulation across spatiotemporal resolutions

Deep brain stimulation is a neuromodulatory treatment for managing the symptoms of Parkinson's disease and other neurological and psychiatric disorders. Electrodes are chronically implanted in disease-relevant brain regions and pulsatile electrical stimulation delivery is intended to restore neurocircuit function. However, the widespread interest in the application and expansion of this clinical therapy has preceded an overarching understanding of the neurocircuit alterations invoked by deep brain stimulation. Over the years, various forms of neurophysiological evidence have emerged which demonstrate changes to brain activity across spatiotemporal resolutions; from single neuron, to local field potential, to brain-wide cortical network effects. Though fruitful, such studies have often led to debate about a singular putative mechanism. In this Update we aim to produce an integrative account of complementary instead of mutually exclusive neurophysiological effects to derive a generalizable concept of the mechanisms of deep brain stimulation. In particular, we offer a critical review of the most common historical competing theories, an updated discussion on recent literature from animal and human neurophysiological studies, and a synthesis of synaptic and network effects of deep brain stimulation across scales of observation, including micro-, meso- and macroscale circuit alterations.

Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography

While resting state electroencephalography (EEG) provides relevant information on pathological changes in Parkinson's disease, most studies focus on the eyes-closed EEG biomarkers. Recent evidence has shown that both eyes-open EEG and reactivity to eyes-opening can also differentiate Parkinson's disease from healthy aging, but no consensus has been reached on a discriminatory capability benchmark. The aim of this study was to determine the resting-state EEG biomarkers suitable for real-time application that can differentiate Parkinson's patients from healthy subjects under both eyes closed and open. For this, we analysed and compared the quantitative EEG analyses of 13 early-stage cognitively normal Parkinson's patients with an age and sex-matched healthy group. We found that Parkinson's disease exhibited abnormal excessive theta activity in eyes-closed, which was reflected by a significantly higher relative theta power, a higher time percentage with a frequency peak in the theta band and a reduced alpha/theta ratio, while Parkinson's patients showed a significantly steeper non-oscillatory spectral slope activity than that of healthy subjects. We also found considerably less alpha and beta reactivity to eyes-opening in Parkinson's disease plus a significant moderate correlation between these EEG-biomarkers and the MDS-UPDRS score, used to assesses the clinical symptoms of Parkinson's Disease. Both EEG recordings with the eyes open and reactivity to eyes-opening provided additional information to the eyes-closed condition. We thus strongly recommend that both eyes open and closed be used in clinical practice recording protocols to promote EEG as a complementary non-invasive screening method for the early detection of Parkinson's disease, which would allow clinicians to design patient-oriented treatment and improve the patient's quality of life.

Electrophysiological damage to neuronal membrane alters ephaptic entrainment

The brain is commonly understood as a complex network system with a particular organization and topology that can result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain's network, ephapticity is a cellular communication mechanism that has received little attention. To understand the network's properties of ephaptic entrainment, we start investigating the ephaptic effect on a single neuron. In this study, we used numerical simulations to examine the relationship between alterations in ephaptic neuronal entrainment and impaired electrophysiological properties of the neuronal membrane, which can occur via spike field coherence (SFC). This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson's or Alzheimer's. To further investigate these phenomena, we proposed a damaged model based on the impairment of both the resistance of the ion channels and the capacitance of the lipid membrane. Therefore, we simulated ephaptic entrainment with the hybrid neural model quadratic integrate-and-fire ephaptic (QIF-E), which mimics an ephaptic entrainment generated by an LFP (simulate a neuronal group). Our results indicate a link between peak entrainment (ephapticity) preference and a shift in frequency band when damage occurs mainly in ion channels. Finally, we discuss possible relationships between ephaptic entrainment and neurodegenerative diseases associated with aging factors.

Coordination Rigidity in the Gait, Posture, and Speech of Persons with Parkinson's Disease

Parkinson's disease (PD) is associated with reduced coordination abilities. These can result either in random or rigid patterns of movement. The latter, described here as coordination rigidity (CR), have been studied less often. We explored whether CR was present in gait, quiet stance, and speech-tasks involving coordination among multiple joints and muscles. Kinematic and voice recordings were used to compute measures describing the dynamics of systems with multiple degrees of freedom and nonlinear interactions. After clinical evaluation, patients with moderate stage PD were compared against matched healthy participants. In the PD group, gait dynamics was associated with decreased dynamic divergence-lower instability-in the vertical axis. Postural fluctuations were associated with increased regularity in the anterior-posterior axis, and voice dynamics with increased predictability, all consistent with CR. The clinical relevance of CR was confirmed by showing that some of those features contribute to disease classification with supervised machine learning (82/81/85% accuracy/sensitivity/specificity).

Beta Oscillations in Monkey Striatum Encode Reward Prediction Error Signals

Reward prediction error (RPE) signals are crucial for reinforcement learning and decision-making as they quantify the mismatch between predicted and obtained rewards. RPE signals are encoded in the neural activity of multiple brain areas, such as midbrain dopaminergic neurons, prefrontal cortex, and striatum. However, it remains unclear how these signals are expressed through anatomically and functionally distinct subregions of the striatum. In the current study, we examined to which extent RPE signals are represented across different striatal regions. To do so, we recorded local field potentials (LFPs) in sensorimotor, associative, and limbic striatal territories of two male rhesus monkeys performing a free-choice probabilistic learning task. The trial-by-trial evolution of RPE during task performance was estimated using a reinforcement learning model fitted on monkeys' choice behavior. Overall, we found that changes in beta band oscillations (15-35 Hz), after the outcome of the animal's choice, are consistent with RPE encoding. Moreover, we provide evidence that the signals related to RPE are more strongly represented in the ventral (limbic) than dorsal (sensorimotor and associative) part of the striatum. To conclude, our results suggest a relationship between striatal beta oscillations and the evaluation of outcomes based on RPE signals and highlight a major contribution of the ventral striatum to the updating of learning processes.SIGNIFICANCE STATEMENT Reward prediction error (RPE) signals are crucial for reinforcement learning and decision-making as they quantify the mismatch between predicted and obtained rewards. Current models suggest that RPE signals are encoded in the neural activity of multiple brain areas, including the midbrain dopaminergic neurons, prefrontal cortex and striatum. However, it remains elusive whether RPEs recruit anatomically and functionally distinct subregions of the striatum. Our study provides evidence that RPE-related modulations in local field potential (LFP) power are dominant in the striatum. In particular, they are stronger in the rostro-ventral rather than the caudo-dorsal striatum. Our findings contribute to a better understanding of the role of striatal territories in reward-based learning and may be relevant for neuropsychiatric and neurologic diseases that affect striatal circuits.

Elevated Gaussian-modeled beta power in the cortex characterizes aging, but not Parkinson's disease

Aging is a key risk factor for the development of Parkinson's disease (PD). PD is characterized by excessive synchrony of beta oscillations (13-30 Hz) in the basal ganglia thalamo-cortical network. However, cortical beta power is not reliably elevated in individuals with PD. Here, we sought to disentangle how resting cortical beta power compares in younger controls, older controls, and individuals with PD using scalp electroencephalogram (EEG) and a novel approach for quantifying beta power. Specifically, we used a Gaussian model to determine if sensorimotor beta power distinguishes these groups. In addition, we looked at the distribution of beta power across the entire cortex. Our findings showed that Gaussian-modeled beta power does not differentiate individuals with PD (on medication) from healthy younger or older controls in sensorimotor cortex. However, beta power (and not theta or alpha) was higher in healthy older versus younger controls. This effect was most pronounced in regions near sensorimotor cortex including the frontal and parietal areas [P < 0.05, false discovery rate (FDR) corrected]. In addition, the bandwidth of the periodic beta was also higher in healthy older than young individuals in parietal regions. Finally, the aperiodic component, specifically the exponent of the signal, was higher (steeper) in younger controls than in individuals with PD in the right parietal-occipital region (P < 0.05, FDR corrected), possibly reflecting differences in neuronal spiking. Our findings suggest that cortical Gaussian beta power is possibly modulated by age and could be further explored in longitudinal studies to determine whether sensorimotor beta increases with increasing age.NEW & NOTEWORTHY Altered sensorimotor beta activity has been shown to be a feature in aging and PD. Using a novel approach, we clarify that resting sensorimotor beta power does not distinguish subjects with PD from healthy younger and older controls. However, beta power was higher in older compared with younger controls in central sensorimotor, frontal, and parietal regions. These results provide a clearer picture of sensorimotor beta power, demonstrating that it is elevated in aging but not PD.

Neural pathway connectivity and discharge changes between M1 and STN in hemiparkinsonian rats

Alterations of electrophysiological activities, such as changed spike firing rates, reshaping the firing patterns, and aberrant frequency oscillations between the subthalamic nucleus (STN) and the primary motor cortex (M1), are thought to contribute to motor impairment in Parkinson's disease (PD). However, the alterations of electrophysiological characteristics of STN and M1 in PD are still unclear, especially under specific treadmill movement. To examine the relationship between electrophysiological activity in the STN-M1 pathway, extracellular spike trains and local field potential (LFPs) of STN and M1 were simultaneously recorded during resting and movement in unilateral 6-hydroxydopamine (6-OHDA) lesioned rats. The results showed that the identified STN neurons and M1 neurons exhibited abnormal neuronal activity after dopamine loss. The dopamine depletion altered the LFP power in STN and M1 whatever in rest or movement states. Furthermore, the enhanced synchronization of LFP oscillations after dopamine loss was found in 12-35 Hz (beta frequencies) between the STN and M1 during rest and movement. In addition, STN neurons were phase-locked firing to M1 oscillations at 12-35 Hz during rest epochs in 6-OHDA lesioned rats. The dopamine depletion also impaired the anatomical connectivity between the M1 and STN by injecting anterograde neuroanatomical tracing virus into M1 in control and PD rats. Collectively, impairment of' electrophysiological activity and anatomical connectivity in the M1-STN pathway may be the basis for dysfunction of the cortico-basal ganglia circuit, correlating with motor symptoms of PD.

Disturbance of functional brain networks and cognitive decline in Parkinson's disease: Severe cerebral small vessel disease aggravates this relationship

INTRODUCTION

Several studies have identified a relationship between functional brain network disturbance and cognitive decline in people with Parkinson's disease (PwP); however, few studies have explored whether cerebral small vessel disease (CSVD) burden modifies this relationship. This study aimed to investigate the potential moderating effect of CSVD on the relationship between functional brain network disturbance and cognitive decline in PwP.

METHODS

We prospectively recruited 61 PwP from Beijing Tiantan Hospital between October 2021 to September 2022. The Montreal Cognitive Assessment (MoCA) score was used to assess cognition. CSVD imaging markers were evaluated following the STandards for ReportIng Vascular changes on nEuroimaging instructions, and the CSVD burden score was calculated. The functional connectivity indicator was obtained and calculated using quantitative electroencephalography examination. The moderating effect of CSVD burden on the relationship between functional brain network disturbance and cognitive decline was examined using hierarchical linear regression.

RESULTS

Forty-six of 61 (75.4%) PwP had cognitive impairment. Higher global weighted phase lag index (wPLI) values in beta1 bands were significantly associated with lower adjusted MoCA scores. CSVD burden aggravated the effect of the global wPLI in beta1 bands on adjusted MoCA scores. This effect was reinforced by the high level of CSVD burden.

CONCLUSIONS

Higher wPLI indicates a possible pathological activation of functional brain networks that are associated with cognitive decline in PwP, and the high level of CSVD burden aggravates this relationship.

Distinctive Effects of D1 and D2 Receptor Agonists on Cortico-Basal Ganglia Oscillations in a Rodent Model of L-DOPA-Induced Dyskinesia

L-DOPA-induced dyskinesia (LID) in Parkinson's disease has been linked to oscillatory neuronal activities in the cortico-basal ganglia network. We set out to examine the pattern of cortico-basal ganglia oscillations induced by selective agonists of D1 and D2 receptors in a rat model of LID. Local field potentials were recorded in freely moving rats using large-scale electrodes targeting three motor cortical regions, dorsomedial and dorsolateral striatum, external globus pallidus, and substantial nigra pars reticulata. Abnormal involuntary movements were elicited by the D1 agonist SKF82958 or the D2 agonist sumanirole, while overall motor activity was quantified using video analysis (DeepLabCut). Both SKF82958 and sumanirole induced dyskinesia, although with significant differences in temporal course, overall severity, and body distribution. The D1 agonist induced prominent narrowband oscillations in the high gamma range (70-110 Hz) in all recorded structures except for the nigra reticulata. Additionally, the D1 agonist induced strong functional connectivity between the recorded structures and the phase analysis revealed that the primary motor cortex (forelimb area) was leading a supplementary motor area and striatum. Following treatment with the D2 agonist, narrowband gamma oscillations were detected only in forelimb motor cortex and dorsolateral striatum, while prominent oscillations in the theta band occurred in the globus pallidus and nigra reticulata. Our results reveal that the dyskinetic effects of D1 and D2 receptor agonists are associated with distinct patterns of cortico-basal ganglia oscillations, suggesting a recruitment of partially distinct networks.

Association between Beta Oscillations from Subthalamic Nucleus and Quantitative Susceptibility Mapping in Deep Gray Matter Structures in Parkinson's Disease

This study aimed to investigate the association between beta oscillations and brain iron deposition. Beta oscillations were filtered from the microelectrode recordings of local field potentials (LFP) in the subthalamic nucleus (STN), and the ratio of the power spectral density of beta oscillations (PSDXb) to that of the LFP signals was calculated. Iron deposition in the deep gray matter (DGM) structures was indirectly assessed using quantitative susceptibility mapping (QSM). The Unified Parkinson's Disease Rating Scale (UPDRS), part III, was used to assess the severity of symptoms. Spearman correlation coefficients were applied to assess the associations of PSDXb with QSM values in the DGM structures and the severity of symptoms. PSDXb showed a significant positive correlation with the average QSM values in DGM structures, including caudate and substantia nigra (SN) (p = 0.008 and 0.044). Similarly, the PSDXb showed significant negative correlations with the severity of symptoms, including axial symptoms and the gait in the medicine-off state (p = 0.006 for both). The abnormal iron metabolism in the SN and striatum pathways may be one of the underlying mechanisms for the occurrence of abnormal beta oscillations in the STN, and beta oscillations may serve as important pathophysiological biomarkers of PD.

Synaptic determinants of cholinergic interneurons hyperactivity during parkinsonism

Parkinson’s disease is a neurodegenerative ailment generated by the loss of dopamine in the basal ganglia, mainly in the striatum. The disease courses with increased striatal levels of acetylcholine, disrupting the balance among these modulatory transmitters. These modifications disturb the excitatory and inhibitory balance in the striatal circuitry, as reflected in the activity of projection striatal neurons. In addition, changes in the firing pattern of striatal tonically active interneurons during the disease, including cholinergic interneurons (CINs), are being searched. Dopamine-depleted striatal circuits exhibit pathological hyperactivity as compared to controls. One aim of this study was to show how striatal CINs contribute to this hyperactivity. A second aim was to show the contribution of extrinsic synaptic inputs to striatal CINs hyperactivity. Electrophysiological and calcium imaging recordings in Cre-mice allowed us to evaluate the activity of dozens of identified CINs with single-cell resolution in ex vivo brain slices. CINs show hyperactivity with bursts and silences in the dopamine-depleted striatum. We confirmed that the intrinsic differences between the activity of control and dopamine-depleted CINs are one source of their hyperactivity. We also show that a great part of this hyperactivity and firing pattern change is a product of extrinsic synaptic inputs, targeting CINs. Both glutamatergic and GABAergic inputs are essential to sustain hyperactivity. In addition, cholinergic transmission through nicotinic receptors also participates, suggesting that the joint activity of CINs drives the phenomenon; since striatal CINs express nicotinic receptors, not expressed in striatal projection neurons. Therefore, CINs hyperactivity is the result of changes in intrinsic properties and excitatory and inhibitory inputs, in addition to the modification of local circuitry due to cholinergic nicotinic transmission. We conclude that CINs are the main drivers of the pathological hyperactivity present in the striatum that is depleted of dopamine, and this is, in part, a result of extrinsic synaptic inputs. These results show that CINs may be a main therapeutic target to treat Parkinson’s disease by intervening in their synaptic inputs.

A striatal SOM-driven ChAT-iMSN loop generates beta oscillations and produces motor deficits

Enhanced beta oscillations within the cortico-basal ganglia-thalamic (CBT) network are correlated with motor deficits in Parkinson's disease (PD), whose generation has been associated recently with amplified network dynamics in the striatum. However, how distinct striatal cell subtypes interact to orchestrate beta oscillations remains largely unknown. Here, we show that optogenetic suppression of dopaminergic control over the dorsal striatum (DS) elevates the power of local field potentials (LFPs) selectively at beta band (12-25 Hz), accompanied by impairments in locomotion. The amplified beta power originates from a striatal loop driven by somatostatin-expressing (SOM) interneurons and constituted by choline acetyltransferase (ChAT)-expressing interneurons and dopamine D2 receptor (D2R)-expressing medium spiny neurons (iMSNs). Moreover, closed-loop intervention selectively targeting striatal iMSNs or ChATs diminishes beta oscillations and restores motor function. Thus, we reveal a striatal microcircuit motif that underlies beta oscillation generation and accompanied motor deficits upon perturbation of dopaminergic control over the striatum.

Separating the aperiodic and periodic components of neural activity in Parkinson's disease

Most studies on electrophysiology have not separated aperiodic activity from the spectra but have rather evaluated a combined periodic oscillatory component and the aperiodic component. As the understanding of aperiodic activity gradually deepens, its potential physiological significance has acquired increased appreciation. Herein, we investigated the two components in scalp electroencephalogram in 16 healthy controls and 15 patients with Parkinson's disease (PD); the results revealed that aperiodic parameters were approximately symmetrically distributed in topography in patients with PD and were significantly modulated by dopaminergic medication in channels C4, C3, CP5 and FC5. In sum, our findings might provide indicators for evaluating treatment response in PD and highlight the importance of re-evaluating the neuronal power spectra parameterization.

Motivated for movement: Beta activation over the motor cortex resulting from intrinsic and extrinsic motivators

Past work on motivation has primarily studied dichotomous distinctions of motivation (e.g., extrinsic or intrinsic). However, focusing on the overall motivational intensity may be better at accentuating the unique differences within and between varying motivators as it pertains to the impetus to act. Specifically, motivational intensity influences neural patterns of beta band frequency (13-30 Hz) as measured by electroencephalography (EEG) that enable motor-action preparation, a neural correlate of motivated movement. The primary aim of across three experiments was to investigate neural motor-action preparation to modified flanker tasks within achievement (Experiment 1), autonomous (Experiment 2), and extrinsic vs. intrinsic (Experiment 3) motivational contexts. Experiment 1 revealed greater motor-action preparation for challenging trial cues and did not differ in behavioral attentional and performance measures across both trial types. Experiment 2 revealed no significant difference in motor-action preparation, did not differ in behavioral attentional narrowing and had worse behavioral performance in high autonomy relative to low autonomy trials. Experiment 3 revealed greater motor-action preparation for challenging trial cues, did not differ in behavioral attentional narrowing and had a faster performance for reward trials relative to high autonomy trials. These findings suggest motivators of the same category (i.e., intrinsic) may differ in motivational strength, as suggested by a neurophysiological measure of immediate motivated movement planning.

Excitatory deep brain stimulation quenches beta oscillations arising in a computational model of the subthalamo-pallidal loop

Parkinson’s disease (PD) is associated with abnormal \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β band oscillations (13–30 Hz) in the cortico-basal ganglia circuits. Abnormally increased striato-pallidal inhibition and strengthening the synaptic coupling between subthalamic nucleus (STN) and globus pallidus externa (GPe), due to the loss of dopamine, are considered as the potential sources of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations in the basal ganglia. Deep brain stimulation (DBS) of the basal ganglia subregions is known as a way to reduce the pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations and motor deficits related to PD. Despite the success of the DBS, its underlying mechanism is poorly understood and, there is controversy about the inhibitory or excitatory role of the DBS in the literature. Here, we utilized a computational network model of basal ganglia which consists of STN, GPe, globus pallidus interna, and thalamic neuronal population. This model can reproduce healthy and pathological \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations similar to what has been observed in experimental studies. Using this model, we investigated the effect of DBS to understand whether its effect is excitatory or inhibitory. Our results show that the excitatory DBS is able to quench the pathological synchrony and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β oscillations, while, applying inhibitory DBS failed to quench the PD signs. In light of simulation results, we conclude that the effect of the DBS on its target is excitatory.

Proximal CA1 20-40 Hz power dynamics reflect trial-specific information processing supporting nonspatial sequence memory

The hippocampus is known to play a critical role in processing information about temporal context. However, it remains unclear how hippocampal oscillations are involved, and how their functional organization is influenced by connectivity gradients. We examined local field potential activity in CA1 as rats performed a nonspatial odor sequence memory task. We found that odor sequence processing epochs were characterized by distinct spectral profiles and proximodistal CA1 gradients of theta and 20-40 Hz power than track running epochs. We also discovered that 20-40 Hz power was predictive of sequence memory performance, particularly in proximal CA1 and during the plateau of high power observed in trials in which animals had to maintain their decision until instructed to respond. Altogether, these results provide evidence that dynamics of 20-40 Hz power along the CA1 axis are linked to trial-specific processing of nonspatial information critical to order judgments and are consistent with a role for 20-40 Hz power in gating information processing.

Control of coupled neural oscillations using near-periodic inputs

Deep brain stimulation (DBS) is a commonly used treatment for medication resistant Parkinson's disease and is an emerging treatment for other neurological disorders. More recently, phase-specific adaptive DBS (aDBS), whereby the application of stimulation is locked to a particular phase of tremor, has been proposed as a strategy to improve therapeutic efficacy and decrease side effects. In this work, in the context of these phase-specific aDBS strategies, we investigate the dynamical behavior of large populations of coupled neurons in response to near-periodic stimulation, namely, stimulation that is periodic except for a slowly changing amplitude and phase offset that can be used to coordinate the timing of applied input with a specified phase of model oscillations. Using an adaptive phase-amplitude reduction strategy, we illustrate that for a large population of oscillatory neurons, the temporal evolution of the associated phase distribution in response to near-periodic forcing can be captured using a reduced order model with four state variables. Subsequently, we devise and validate a closed-loop control strategy to disrupt synchronization caused by coupling. Additionally, we identify strategies for implementing the proposed control strategy in situations where underlying model equations are unavailable by estimating the necessary terms of the reduced order equations in real-time from observables.

Novel approaches for quantifying beta synchrony in Parkinson's disease

Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30 Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50 Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.

Electrophysiological Signature and the Prediction of Deep Brain Stimulation Withdrawal and Insertion Effects

Deep brain stimulation (DBS) serves as a treatment for neurological and psychiatric disorders, such as Parkinson's disease (PD), essential tremor, dystonia, Tourette Syndrome (GTS), Huntington's disease, and obsessive-compulsive disorder (OCD). There is broad experience with the short-term effects of DBS in individual diseases and their signs/symptoms. However, even in acute treatment and for the same disorder or a given disorder, a prediction of effect is not perfect. Even further, the factors that influence the long-term effect of DBS and its withdrawal are hardly characterized. In this work, we aim to shed light on an important topic, the question of “DBS dependency.” To address this, we make use of the Kuramoto model of phase synchronization (oscillation feature) endowed with neuroplasticity to study the effects of DBS under successive withdrawals and renewals of neuromodulation as well as influence of treatment duration in de novo DBS “patients.” The results of our simulation show that the characteristics of neuroplasticity have a profound effect on the stability and mutability of oscillation synchronization patterns across successive withdrawal and renewal of DBS in chronic “patients” and also in de novo DBS “patients” with varying duration of treatment (here referred to as the “number of iterations”). Importantly, the results demonstrate the strong effect of the individual neuroplasticity makeup on the behavior of synchrony of oscillatory activity that promotes certain disorder/disease states or symptoms. The effect of DBS-mediated neuromodulation and withdrawal is highly dependent on the makeup of the neuroplastic signature of a disorder or an individual.

Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations

Βeta oscillatory activity (human: 13-35 Hz; primate: 8-24 Hz) is pervasive within the cortex and basal ganglia. Studies in Parkinson's disease patients and animal models suggest that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine tone remains unclear. We recorded neural activity in the cortex and basal ganglia of healthy non-human primates while acutely and chronically up- and down-modulating dopamine levels. We assessed changes in beta oscillations in patients with Parkinson's following acute and chronic changes in dopamine tone. Here we show beta oscillation frequency is strongly coupled with dopamine tone in both monkeys and humans. Power, coherence between single-units and local field potentials (LFP), spike-LFP phase-locking, and phase-amplitude coupling are not systematically regulated by dopamine levels. These results demonstrate that beta frequency is a key property of pathological oscillations in cortical and basal ganglia networks.

Mathematical model of subthalamic nucleus neuron: Characteristic activity patterns and bifurcation analysis

The subthalamic nucleus (STN) has an important role in the pathophysiology of the basal ganglia in Parkinson's disease. The ability of STN cells to generate bursting rhythms under either transient or sustained hyperpolarization may underlie the excessively synchronous beta rhythms observed in Parkinson's disease. In this study, we developed a conductance-based single compartment model of an STN neuron, which is able to generate characteristic activity patterns observed in experiments including hyperpolarization-induced bursts and post-inhibitory rebound bursts. This study focused on the role of three currents in rhythm generation: T-type calcium (CaT) current, L-type calcium (CaL) current, and hyperpolarization-activated cyclic nucleotide-gated (HCN) current. To investigate the effects of these currents in rhythm generation, we performed a bifurcation analysis using slow variables in these currents. Bifurcation analysis showed that the HCN current promotes single-spike activity patterns rather than bursting in agreement with experimental results. It also showed that the CaT current is necessary for characteristic bursting activity patterns. In particular, the CaT current enables STN neurons to generate these activity patterns under hyperpolarizing stimuli. The CaL current enriches and reinforces these characteristic activity patterns. In hyperpolarization-induced bursts or post-inhibitory rebound bursts, the CaL current allows STN neurons to generate long bursting patterns. Thus, the bifurcation analysis explained the synergistic interaction of the CaT and CaL currents, which enables STN neurons to respond to hyperpolarizing stimuli in a salient way. The results of this study implicate the importance of CaT and CaL currents in the pathophysiology of the basal ganglia in Parkinson's disease.

A Systematic Review of Neurofeedback for the Management of Motor Symptoms in Parkinson's Disease

Background: Neurofeedback has been proposed as a treatment for Parkinson’s disease (PD) motor symptoms by changing the neural network activity directly linked with movement. However, the effectiveness of neurofeedback as a treatment for PD motor symptoms is unclear. Aim: To systematically review the literature to identify the effects of neurofeedback in people with idiopathic PD; as defined by measurement of brain activity; motor function; and performance. Design: A systematic review. Included Sources and Articles: PubMed; MEDLINE; Cinhal; PsychoInfo; Prospero; Cochrane; ClinicalTrials.gov; EMBASE; Web of Science; PEDro; OpenGrey; Conference Paper Index; Google Scholar; and eThos; searched using the Population-Intervention-Comparison-Outcome (PICO) framework. Primary studies with the following designs were included: randomized controlled trials (RCTs), non-RCTs; quasi-experimental; pre/post studies; and case studies. Results: This review included 11 studies out of 6197 studies that were identified from the literature search. Neuroimaging methods used were fMRI; scalp EEG; surface brain EEG; and deep brain EEG; where 10–15 Hz and the supplementary motor area were the most commonly targeted signatures for EEG and fMRI, respectively. Success rates for changing one’s brain activity ranged from 47% to 100%; however, both sample sizes and success criteria differed considerably between studies. While six studies included a clinical outcome; a lack of consistent assessments prevented a reliable conclusion on neurofeedback’s effectiveness. Narratively, fMRI neurofeedback has the greatest potential to improve PD motor symptoms. Two main limitations were found in the studies that contributed to the lack of a confident conclusion: (1) insufficient clinical information and perspectives (e.g., no reporting of adverse events), and (2) limitations in numerical data reporting (e.g., lack of explicit statistics) that prevented a meta-analysis. Conclusions: While fMRI neurofeedback was narratively the most effective treatment; the omission of clinical outcome measures in studies using other neurofeedback approaches limits comparison. Therefore, no single neurofeedback type can currently be identified as an optimal treatment for PD motor symptoms. This systematic review highlights the need to improve the inclusion of clinical information and more robust reporting of numerical data in future work. Neurofeedback appears to hold great potential as a treatment for PD motor symptoms. However, this field is still in its infancy and needs high quality RCTs to establish its effectiveness. Review Registration: PROSPERO (ID: CRD42020191097)

Altered Dynamic Information Flow through the Cortico-Basal Ganglia Pathways Mediates Parkinson's Disease Symptoms

Parkinson’s disease (PD) is a progressive neurodegenerative disorder caused by dopamine deficiency. To elucidate network-level changes through the cortico-basal ganglia pathways in PD, we recorded neuronal activity in PD monkeys treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. We applied electrical stimulation to the motor cortices and examined responses in the internal (GPi) and external (GPe) segments of the globus pallidus, the output and relay nuclei of the basal ganglia, respectively. In the normal state, cortical stimulation induced a triphasic response composed of early excitation, inhibition, and late excitation in the GPi and GPe. In the PD state, cortically evoked inhibition in the GPi mediated by the cortico-striato-GPi “direct” pathway was largely diminished, whereas late excitation in the GPe mediated by the cortico-striato-GPe-subthalamo (STN)-GPe pathway was elongated. l-DOPA treatment ameliorated PD signs, particularly akinesia/bradykinesia, and normalized cortically evoked responses in both the GPi and GPe. STN blockade by muscimol injection ameliorated the motor deficit and unmasked cortically evoked inhibition in the GPi. These results suggest that information flow through the direct pathway responsible for the initiation of movements is largely reduced in PD and fails to release movements, resulting in akinesia/bradykinesia. Restoration of the information flow through the direct pathway recovers execution of voluntary movements.

Cortical Engagement Metrics During Reactive Balance Are Associated With Distinct Aspects of Balance Behavior in Older Adults

Heightened reliance on the cerebral cortex for postural stability with aging is well-known, yet the cortical mechanisms for balance control, particularly in relation to balance function, remain unclear. Here we aimed to investigate motor cortical activity in relation to the level of balance challenge presented during reactive balance recovery and identify circuit-specific interactions between motor cortex and prefrontal or somatosensory regions in relation to metrics of balance function that predict fall risk. Using electroencephalography, we assessed motor cortical beta power, and beta coherence during balance reactions to perturbations in older adults. We found that individuals with greater motor cortical beta power evoked following standing balance perturbations demonstrated lower general clinical balance function. Individual older adults demonstrated a wide range of cortical responses during balance reactions at the same perturbation magnitude, showing no group-level change in prefrontal- or somatosensory-motor coherence in response to perturbations. However, older adults with the highest prefrontal-motor coherence during the post-perturbation, but not pre-perturbation, period showed greater cognitive dual-task interference (DTI) and elicited stepping reactions at lower perturbation magnitudes. Our results support motor cortical beta activity as a potential biomarker for individual level of balance challenge and implicate prefrontal-motor cortical networks in distinct aspects of balance control involving response inhibition of reactive stepping in older adults. Cortical network activity during balance may provide a neural target for precision-medicine efforts aimed at fall prevention with aging.

Gamma-band modulation in the human amygdala during reaching movements

OBJECTIVE

Motor brain-computer interface (BCI) represents a new frontier in neurological surgery that could provide significant benefits for patients living with motor deficits. Both the primary motor cortex and posterior parietal cortex have successfully been used as a neural source for human motor BCI, leading to interest in exploring other brain areas involved in motor control. The amygdala is one area that has been shown to have functional connectivity to the motor system; however, its role in movement execution is not well studied. Gamma oscillations (30-200 Hz) are known to be prokinetic in the human cortex, but their role is poorly understood in subcortical structures. Here, the authors use direct electrophysiological recordings and the classic "center-out" direct-reach experiment to study amygdaloid gamma-band modulation in 8 patients with medically refractory epilepsy.

METHODS

The study population consisted of 8 epilepsy patients (2 men; age range 21-62 years) who underwent implantation of micro-macro depth electrodes for seizure localization and EEG monitoring. Data from the macro contacts sampled at 2000 Hz were used for analysis. The classic center-out direct-reach experiment was used, which consists of an intertrial interval phase, a fixation phase, and a response phase. The authors assessed the statistical significance of neural modulation by inspecting for nonoverlapping areas in the 95% confidence intervals of spectral power for the response and fixation phases.

RESULTS

In 5 of the 8 patients, power spectral analysis showed a statistically significant increase in power within regions of the gamma band during the response phase compared with the fixation phase. In these 5 patients, the 95% bootstrapped confidence intervals of trial-averaged power in contiguous frequencies of the gamma band during the response phase were above, and did not overlap with, the confidence intervals of trial-averaged power during the fixation phase.

CONCLUSIONS

To the authors' knowledge, this is the first time that direct neural recordings have been used to show gamma-band modulation in the human amygdala during the execution of voluntary movement. This work indicates that gamma-band modulation in the amygdala could be a contributing source of neural signals for use in a motor BCI system.

Correlating Beta Oscillations from Intraoperative Microelectrode and Postoperative Implanted Electrode in Patients Undergoing Subthalamic Nucleus Deep Brain Stimulation for Parkinson Disease; A Feasibility Study

OBJECTIVE

We sought to investigate the feasibility of intraoperative local field potential (LFP) recording from the microelectrode during deep brain stimulation surgery for patients with Parkinson disease.

METHODS

Sixteen subthalamic nucleus recordings from 10 Parkinson disease patients who underwent deep brain stimulation surgery were included in this study. Signals from microelectrodes were amplified and differently filtered to display real-time single-unit neuronal activity and LFP simultaneously during surgery. LFP recordings were also recorded postoperatively from the implanted macroelectrodes and, power spectral density and peak frequency of beta oscillation of LFP (beta LFP) between 2 conditions were compared.

RESULTS

Stable intraoperative beta LFP were observed in 68.75% (11 of 16) cases. There was no significant difference of peak frequency between intraoperative and postoperative beta-LFP but significant difference of mean percentage of beta LFP was noted between 2 conditions.

CONCLUSIONS

Despite low signal-to-noise ratio and susceptibility to noises from external sources, this study shows that intraoperative recording of beta LFP using microelectrode is feasible. And, given that no significant difference in peak frequency of beta LFP between intraoperative and postoperative LFP was found, we suggest that not only intraoperative beta LFP can be used as a reliable surrogate for postoperative beta LFP, but it can also provide us an information for estimating the location with maximal power of beta oscillation within the subthalamic nucleus.

Motor network connectivity predicts neuroplastic response following theta burst stimulation in healthy adults

A patterned repetitive transcranial magnetic stimulation protocol, known as continuous theta burst stimulation (cTBS), can suppress corticospinal excitability via mechanisms that appear similar to long-term depression synaptic plasticity. Despite much potential, this technique is currently limited by substantial response variability. The purpose of this study was to investigate whether baseline resting state functional connectivity is a determinant of response to cTBS. Eighteen healthy young adults participated in up to three experimental sessions. Single-pulse transcranial magnetic stimulation was used to quantify change in corticospinal excitability following cTBS. Three minutes of resting electroencephalographic activity was recorded, and functional connectivity was estimated using the debiased weighted phase lag index across different frequency bands. Partial least squares regression identified models of connectivity between a seed region (C3) and the whole scalp that maximally accounted for variance in cTBS responses. There was no group-level effect of a single cTBS train or spaced cTBS trains on corticospinal excitability (p = 0.092). A low beta frequency band model of connectivity accounted for the largest proportion of variance in spaced cTBS response (R² = 0.50). Based on the low beta frequency model, a-priori regions of interest were identified and predicted 39% of variance in response to spaced cTBS at a subsequent session. Importantly, weaker connectivity between the seed electrode (C3) and a cluster approximating a frontocentral region was associated with greater spaced cTBS response (p = 0.02). It appears M1-frontocentral networks may have an important role in determining the effects of cTBS on corticospinal excitability.

Mechanisms of Antiparkinsonian Anticholinergic Therapy Revisited

Before the advent of L-DOPA, the gold standard symptomatic therapy for Parkinson's disease (PD), anticholinergic drugs (muscarinic receptor antagonists) were the preferred antiparkinsonian therapy, but their unwanted side effects associated with impaired extrastriatal cholinergic function limited their clinical utility. Since most patients treated with L-DOPA also develop unwanted side effects such as L-DOPA-induced dyskinesia (LID), better therapies are needed. Recent studies in animal models demonstrate that optogenetic and chemogenetic manipulation of striatal cholinergic interneurons (SCIN), the main source of striatal acetylcholine, modulate parkinsonism and LID, suggesting that restoring SCIN function might serve as a therapeutic option that avoids extrastriatal anticholinergics' side effects. However, it is still unclear how the altered SCIN activity in PD and LID affects the striatal circuit, whereas the mechanisms of action of anticholinergic drugs are still not fully understood. Recent animal model studies showing that SCINs undergo profound changes in their tonic discharge pattern after chronic L-DOPA administration call for a reexamination of classical views of how SCINs contribute to PD symptoms and LID. Here, we review the recent advances on the circuit implications of aberrant striatal cholinergic signaling in PD and LID in an effort to provide a comprehensive framework to understand the effects of anticholinergic drugs and with the aim of shedding light into future perspectives of cholinergic circuit-based therapies.

Bifurcation analyses and potential landscapes of a cortex-basal ganglia-thalamus model

The dynamics of cortical neuronal activity plays important roles in controlling body movement and is regulated by connection weights between neurons in a cortex–basal ganglia–thalamus (BGCT) loop. Beta‐band oscillation of cortical activity is closely associated with the movement disorder of Parkinson's disease, which is caused by an imbalance in the connection weights of direct and indirect pathways in the BGCT loop. In this study, the authors investigate how the dynamics of cortical activity are modulated by connection weights of direct and indirect pathways in the BGCT loop under low dopamine levels through bifurcation analyses and potential landscapes. The results reveal that cortical activity displays rich dynamics under different connection weights, including one, two, or three stable steady states, one or two stable limit cycles, and the coexistence of one stable limit cycle with one stable steady state or two stable ones. For a low dopamine level, cortical activity exhibits oscillation for larger connection weights of direct and indirect pathways. The stability of these stable dynamics is explored by the potential landscapes.

Spectral signatures of L-DOPA-induced dyskinesia depend on L-DOPA dose and are suppressed by ketamine

L-DOPA-induced dyskinesias (LID) are debilitating motor symptoms of dopamine-replacement therapy for Parkinson's disease (PD) that emerge after years of L-DOPA treatment. While there is an abundance of research into the cellular and synaptic origins of LID, less is known about how LID impacts systems-level circuits and neural synchrony, how synchrony is affected by the dose and duration of L-DOPA exposure, or how potential novel treatments for LID, such as sub-anesthetic ketamine, alter this activity. Sub-anesthetic ketamine treatments have recently been shown to reduce LID, and ketamine is known to affect neural synchrony. To investigate these questions, we measured movement and local-field potential (LFP) activity from the motor cortex (M1) and the striatum of preclinical rodent models of PD and LID. In the first experiment, we investigated the effect of the LID priming procedures and L-DOPA dose on neural signatures of LID. Two common priming procedures were compared: a high-dose procedure that exposed unilateral 6-hydroxydopamine-lesioned rats to 12 mg/kg L-DOPA for 7 days, and a low-dose procedure that exposed rats to 7 mg/kg L-DOPA for 21 days. Consistent with reports from other groups, 12 mg/kg L-DOPA triggered LID and 80-Hz oscillations; however, these 80-Hz oscillations were not observed after 7 mg/kg administration despite clear evidence of LID, indicating that 80-Hz oscillations are not an exclusive signature of LID. We also found that weeks-long low-dose priming resulted in the emergence of non-oscillatory broadband gamma activity (> 30 Hz) in the striatum and theta-to-high-gamma cross-frequency coupling (CFC) in M1. In a second set of experiments, we investigated how ketamine exposure affects spectral signatures of low-dose L-DOPA priming. During each neural recording session, ketamine was delivered through 5 injections (20 mg/kg, i.p.) administered every 2 h. We found that ketamine exposure suppressed striatal broadband gamma associated with LID but enhanced M1 broadband activity. We also found that M1 theta-to-high-gamma CFC associated with the LID on-state was suppressed by ketamine. These results suggest that ketamine's therapeutic effects are region specific. Our findings also have clinical implications, as we are the first to report novel oscillatory signatures of the common low-dose LID priming procedure that more closely models dopamine replacement therapy in individuals with PD. We also identify neural correlates of the anti-dyskinetic activity of sub-anesthetic ketamine treatment.

Model-Based Closed-Loop Suppression of Parkinsonian Beta Band Oscillations Through Origin Analysis

Excessive beta band (13-30 Hz) oscillations have been observed in the basal ganglia (BG) of patients with Parkinson's disease (PD). Understanding the origin and transmission of beta band oscillations are important to improve treatments of PD, such as closed-loop deep brain stimulation (DBS). This paper proposed a model-based closed-loop GPi stimulation system to suppress pathological beta band oscillations of BG. The feedback nucleus was selected through the analysis of GPi oscillations variation when different synaptic currents were blocked, mainly projections from globus pallidus external (GPe), the subthalamic nucleus (STN) and striatum. Since simulation results proved the important role of synaptic current from GPe in shaping the excessive GPi beta band oscillations, the local field potential (LFP) of GPe was chosen as the feedback signal. That is to say, the feedback nucleus was selected based on the origin analysis of the pathological GPi beta band oscillation. The closed-loop algorithm was the multiplication of linear delayed feedback of the filtered GPe-LFP and modeled synaptic dynamics from GPe to GPi. Thus, the formed stimulation waveform was synaptic current like shape, which was proved to be more energy efficient than open-loop continuous DBS in suppressing GPi beta band oscillation. With the development of DBS devices, the efficiency of this closed-loop stimulation could be testified in animal model and clinical.